Characterization of an Integrated Three-Way Catalyst/Lean NOx Trap System for Lean Burn SI Engines
Bibliographic record
Abstract
The push for environmental protection and sustainability has led to strict emission regulations for automotive manufacturers as evident in EURO VII and 2026 EPA requirements. The challenge lies in maintaining fuel efficiency and simultaneously reducing the carbon footprint while meeting future emission regulations. Alcohol (primarily methanol, ethanol, and butanol) and ether (dimethyl ether) fuels, owing to their comparable energy density to existing fuels, the comparative ease of handling, renewable production, and suitable emission characteristics may present an attractive drop-in replacement, fully or in part as an additive, to the gasoline/diesel fuels, without extensive modifications to the engine geometry. Additionally, lean and diluted combustion are well-researched pathways for efficiency improvement and reduction of engine-out emissions of modern engines. Modern spark ignition (SI) engines typically employ various in-cylinder emission reduction techniques along with a three-way catalyst (TWC) based exhaust after-treatment system to comply with emission standards. However, the periodic lean-rich oscillations for this TWC system necessitate the SI engine to operate at near stoichiometric mixture conditions, which limits the viability of lean burn for SI engines. Lean NOx trap (LNT) system can reduce the engine out NOx under lean conditions at a cost of fuel efficiency penalty due to regeneration. In the present study, the feasibility of using a coupled TWC-LNT system with extensive dilution to achieve ultra-low tailpipe emissions is investigated. Relevant engine-out exhaust conditions from an SI engine, including flow, temperature, and exhaust species, operating at different dilution conditions were replicated on a heated aftertreatment flow bench. A comprehensive analysis of species before and after the catalyst sections was performed using Fourier-transformed infrared (FTIR) and mass spectrometers to study and quantify the conversion and formation of species, including ammonia, methane, and hydrogen, under different engine-out conditions. The results the integration of LNT to a TWC catalyst improves the conversion efficiency of reducing species during the lean operation period. TWC and LNT catalyst simultaneously achieve high conversion efficiency at ~350°C. The LNT regeneration behavior is noticeably affected by the presence of preceding TWC catalyst. The temperature rise because of the oxidation reactions on TWC can deteriorate the LNT regeneration efficiency beyond 400°C.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".